Skip to content
May 13, 2024

Data Security Platform: A Comprehensive Guide to What It Is and Its Benefits

How do you balance maximum data security with scaling and leveraging data for analytics, marketing, HR management, and revenue generation? Locking up data too tightly can impede these crucial activities. Overly permissive data access, on the other hand, can expose organizations to significant security risks and compliance issues.

A data security platform offers a balanced approach to data security and data access that aligns with business capabilities, not only protecting data from compliance and regulatory threats, but enabling businesses to safely and effectively use data to drive growth and innovation.

What is a Data Security Platform?

Gartner describes a DSP as delivering “most of the required components critical to enabling good data governance and optimized data security controls, while preventing the exponential increase of data access rules by offering a centralized system for policy and permission control.”

In simpler terms, a DSP unifies data discovery, protection, and control in a single solution. It helps security teams monitor and control access to sensitive data, reducing the risk of unauthorized access. It integrates data from various sources to provide a holistic view of an organization’s security environment, identifying potential threats and risks while providing better insight into the context in which security events occur.

  • Discovery. In order to classify its data, organizations must be able to find it wherever it resides, including files, databases, or in the cloud.
  • Protection. Once sensitive data is discovered, businesses can secure it with protective measures like encryption or tokenization.
  • Control. Data security regulations and mandates require companies to monitor, detect, control, and report on authorized and unauthorized data access and encryption keys. A DSP centrally manages encryption keys and configures security policies for controlling sensitive information on-premise, in the cloud, and across hybrid environments.

By implementing strong data access restrictions and security controls, companies can safely expose and share more of their data, allowing them to make better use of it to improve strategies and achieve business goals. DSPs that tightly integrate security controls with business rules and fine-grained authorization lead to significant gains in both data protection effectiveness and data utilization. For instance, a healthcare provider could share patient data across departments for better coordination of care while ensuring regulatory compliance.

Six key capabilities of an integrated DSP include:

  1. Fine-grained access control. Unlike basic access control, fine-grained access control adapts to specific needs by considering various factors before granting data access. This flexibility means access rights can be finely tuned to align with individual roles and specific business rules. Capabilities like policy-based access control (PBAC) allow for precise and dynamic permissions, helping to eliminate data silos via consistent application of security policies across the organization while also facilitating secure and immediate data access as required by data-driven businesses.
  2. Data discovery and classification. Tapping into metadata from existing databases or data catalogs enables data tagging and ensures it is easily searchable and organized by sensitivity levels. Integrating this feature directly into the data security platform simplifies the implementation of tag-based access controls and automates security policy enforcement. This integrated approach enhances operational efficiencies and streamlines the overall data security architecture.
  3. Data masking and encryption. Rather than using siloed masking and encryption, DSPs provide a unified strategy for consistent data obfuscation across all of your technologies. This facilitates consistent deployment of data security governance policies and prevents inefficiencies and inconsistencies.
  4. Data security and risk insights. As the central hub for data security management, a DSP offers unified auditing, reporting, and visibility into sensitive data locations, access patterns, and potential risks, enabling informed decision-making.
  5. Workflows, policy orchestration, and automation. DSPs automate complex processes like compliance workflows and policy implementation, boosting efficiency, reducing errors, and accelerating compliance.
  6. Data governance integration. A DSP must be capable of integrating into an organization’s broader data governance infrastructure, ensuring seamless user access control and enabling rapid, secure data access.

How a Data Security Platform Simplifies Data Protection

A DSP’s configurability and scalability mean it can easily accommodate a business’s evolving needs. Unlike a data protection platform that ensures data can be recovered in the event of a disaster, a data security platform prioritizes sensitive information protection and enforcing security policies. This crucial capability prevents unauthorized access and threats while facilitating secure data access tailored to a business’s requirements.

By providing a centralized solution to managing evolving security challenges, a DSP also helps minimize the risk of security breaches caused by inconsistent or fragmented security policies and configurations. Implementing a unified security strategy helps organizations better assess and address their overall security posture, reducing the likelihood of security incidents and minimizing the potential impact of any breaches that do occur.

A DSP often incorporates automation capabilities, which can significantly improve the efficiency and speed of security operations. Automated processes monitor and track security events, identify anomalies, and initiate appropriate responses to potential threats, reducing the risk of human error and ensuring timely action in the event of a security incident.

Artificial Intelligence & Machine Learning in Data Security

Data security platforms are increasingly leveraging AI and ML technologies to enhance their capabilities and provide more robust protection against evolving cyber threats. One of their key data security applications is user behavior analytics (UBA) that analyzes user activities and patterns to detect anomalous behavior that could indicate a potential security breach or insider threat.

  • ML algorithms help in establishing baselines of normal user behavior and then identify deviations from these baselines, such as unusual login times, access to sensitive data, or out of the ordinary data transfer patterns. Security teams can then quickly investigate and respond to potential threats before they escalate.
  • AI and ML are revolutionizing data security by automating policy management and replacing static, predefined rules with dynamic adjustments to security policies based on ongoing analysis of data trends and anomalies. Continuously learning from network traffic, system logs, and user activities allows the technologies to adapt and enforce policies that effectively respond to new and evolving threats, ensuring that security measures are always aligned with the current threat landscape.
  • Automated permission management systems within a DSP dynamically adjust user access and permissions as changes occur within the organization. For instance, when a user’s role or responsibilities shift, the system automatically detects these changes and updates their permissions accordingly.

As cyber threats continue to evolve, AI and ML technologies help protect sensitive information by adapting and learning from new data and patterns, assisting organization in maintaining a robust security posture.

Risk Reduction

While the cloud offers enormous benefits in data protection, it also poses unique security challenges, including shared responsibility models, data sovereignty, and the need for visibility across multi-cloud environments. A 2023 survey found that over 80% of breaches involved data stored in the cloud, exposing billions of personal records. A DSP reduces these and other risks, providing a holistic and integrated solution to security challenges that include:

  • Managing cloud security. A DSP secures sensitive data stored in multi-cloud environments, including public and private clouds.
  • Mitigating data loss. By monitoring data access, a DSP supports an organization’s data loss prevention policies.
  • Preventing data theft. As cloud storage becomes the method of choice, the risk of data theft continues to rise. A DSP enhances security by employing data masking and encryption techniques to obscure or securely encode sensitive information, making it inaccessible to unauthorized users. Only individuals with the appropriate permissions can access or view the data in its true form, significantly reducing the risk of data theft.
  • Meeting compliance mandates. A DSP’s policy management capabilities ensure  businesses comply with mandates like GDPR, HIPAA, CCPA, and PCI DSS.

By finding and eliminating active threats like unauthorized access and other data breaches, a DSP helps security teams respond more quickly and reduce a security incident’s impact.

Benefits of a Data Security Platform

Aside from risk reduction, a DSP offers strategic business and platform advantages for organizations wanting to operate more securely and efficiently.

  1. Reduced operational costs. Automating critical security processes cuts down on the time and money spent on data security.
  2. Improved efficiency. By integrating multiple security measures and technologies into a single, comprehensive solution, security teams don’t need to manage multiple-point solutions.
  3. Enhanced reputation. Data security is a vital component of the customer experience, much more so than even a decade ago. By implementing a DSP, organizations can improve their reputation and build trust with customers, partners, and other stakeholders.
  4. Informed decisions. DSPs provide visibility into who is accessing sensitive data, when they’re accessing it, and from where, information that can be used to improve security and make informed business decisions.
  5. Improved business continuity. Productivity is maintained during a data loss incident or other security event, reducing risk and enhancing resilience.

As a Gartner Guide-recognized data security platform, Velotix empowers organizations to protect their data. It creates full-scale visibility into potential threats, helping to mitigate data risks like ransomware, unauthorized access, and data corruption. It classifies regulated data to ensure compliance and detects and responds to attacks in real-time, preventing data exfiltration and theft.

A game-changer in stopping threats in their tracks, Velotix integrates easily with other security tools to provide a more holistic and unified approach to security monitoring, incident response, and threat mitigation. And, as the only AI-based data security platform that automatically grants the right access to the right data at the right time, it ensures a secure future where data is always protected, always compliant, and always accessible to the right people.

NEW GEN AI

Get answers to even the most complex questions about your data and explore the complexities of your data landscape using Generative AI chat.